Autism is a severe neurodevelopmental disorder characterized by marked social and communication deficits, restricted and stereotyped patterns of behaviors and interests with evidence supporting its neurobiologic and polygenic basis. The proposed study will build on an ongoing NIMH-funded study (R01 MH 067005 A population-based twin study of autism in California PI: Joachim Hallmayer). The existence of this population-based study of twins, with at least one twin with autism, will provide unprecedented opportunities to examine the relative impact of genetic and nongenetics factors on brain anatomy and chemistry in autism. Specifically, from this sample of more than 120 twin pairs who completed the genetic study to date, we will randomly recruit 80 same-sex autism twin pairs, 40 MZ and 40 DZ. We will also recruit 40 typically developing same-sex twin pair controls, 20 MZ and 20 DZ, group-matched to the sample comprised by the 80 autistic (twin) probands for age, gender, and socioeconomic status. High resolution anatomical, diffusion tensor and proton spectroscopy scans will be obtained from all participants. All new data collected in this study will be evaluated in the context of extensive cognitive and behavioral measures available from the ongoing NIMH study described above. We also will collect additional clinical measures at the time of the proposed imaging investigation to provide more specific covariates for neuroanatomical and neurochemical variables. The overarching goal is to develop a better understanding of linkages among clinical features and neurobiological measures in individuals affected by autism, thus allowing the identification of clinical or biological endophenotypes that will lead to a better characterization and understanding of this disorder. Twin studies in autism are particularly informative for examining the relative contribution of genetic and environmental risk factors to neurobiologic variations observed in this disorder. Improving our understanding of the neurobiology of autism and brain behavior correlations will help in the development of better procedures for predicting outcome and the design and implementation of more targeted therapeutic approaches.